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* Start structural rework on constraint objectives. * Sketch the idea of a unified vector function objective. * Fix tests. * A bit of vale. * Update Changelog. * Sketch Hessian vector function. * add type upper bounds to ConstrainedManifoldObjective * Apply suggestions from code review * minor improvements --------- Co-authored-by: Mateusz Baran <mateuszbaran89@gmail.com>
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# [Proximal Bundle Method](@id ProxBundleMethodSolver) | ||
# Proximal bundle method | ||
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```@meta | ||
CurrentModule = Manopt | ||
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@JuliaRegistrator register
Release Notes:
Added
VectorGradientFunctions
to reduce code duplication and encapsulate the inner model of these functions and their gradients
ConstrainedManoptProblem
to model different ranges for the gradients in thenew
VectorGradientFunction
s beyond the defaultNestedPowerRepresentation
VectorHessianFunction
to also model that one can provide the vector of Hessiansto constraints
when accessing vector functions and their gradients and hence also for constraints and
their gradients.
Changed
ConstrainedManifoldObjective
to store anAbstractManifoldObjective
internally instead of directly
f
andgrad_f
, allowing also Hessian objectivestherein and implementing access to this Hessian
Deprecated
get_grad_equality_constraints(M, o, p)
, useget_grad_equality_constraint(M, o, p, :)
from the more flexible indexing instead.
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Registration pull request created: JuliaRegistries/General/108549
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